Gas leakage alarm linkage monitoring method and system for gas meter

Abstract

The application relates to the technical field of safety monitoring, and discloses a linkage monitoring method and system for a gas leakage alarm and a gas meter, which comprises the following steps: periodically regulating the temperature of a gas sensor, obtaining monitoring values under different temperatures and calculating a ratio, and identifying gas leakage and non-leakage gas sources; when it is determined that leakage occurs, a camera is activated to shoot a gas meter counter image and to synchronously collect temperature and pressure data, which are uploaded to a data processing center; a gas consumption value is extracted based on an image recognition algorithm, environmental interference is corrected in combination with an ideal gas state equation and a dynamic compensation model, and high-precision gas consumption is generated; and through analysis of the time sequence correlation between the corrected consumption and a leakage signal, if abnormal conditions are met, a valve is automatically closed and an alarm is given. The application can realize high-precision, low false alarm and fast response of gas leakage detection.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of safety monitoring, in particular to a linkage monitoring method and system of a gas leakage alarm and a gas meter. BACKGROUND

[0002] In the existing gas safety monitoring technology, the gas meter relies on a flow sensor (such as a rotating sub-pulse signal) to measure the gas consumption, but such a sensor is easily affected by environmental noise, installation position deviation and external electromagnetic interference, resulting in a significant difference between the measured value and the actual display value, which may further mask the gas leakage signal and cause a missed detection risk.

[0003] A similar prior art is Chinese patent application No. CN118168725A, which discloses a gas leakage monitoring method, device, system and medium based on a gas meter. It includes sending a connection instruction to a target gas meter and determining whether the target gas meter is successfully connected. If the target gas meter is not successfully connected, the inlet pressure corresponding to the gas inlet of the target gas meter, the first pressure corresponding to the first preset position and the second pressure of the second preset position are obtained. The first pressure difference between the first pressure and the inlet pressure, and the second pressure difference between the second pressure and the first pressure are determined, and it is determined whether the first pressure difference or the second pressure difference is greater than the preset pressure difference. If the first pressure difference or the second pressure difference is greater than the preset pressure difference, an alarm information is sent. However, this application only determines the leakage by the pressure difference, and the response to slow leakage is slow, and a high leakage amount is required to trigger the alarm.

[0004] A similar prior art is Chinese patent application No. CN118823980A, which discloses a gas leakage detection method and device based on an Internet of Things intelligent gas meter. The method includes outputting a high-level signal from the first port of a single-chip microcomputer and receiving a first-level signal from the second port of the single-chip microcomputer. The single-chip microcomputer determines the receiving frequency according to the first-level signal, and the second port of the single-chip microcomputer receives at least one second-level signal according to the receiving frequency. The single-chip microcomputer determines the leakage state of the gas according to all second-level signals, and when the gas is in the leakage state, the first port of the single-chip microcomputer outputs a low-level signal. However, this application can only determine "leakage or no leakage", cannot quantify the concentration or gas composition, and has low detection accuracy. SUMMARY

[0005] To solve the above technical problems, the present application provides a linkage monitoring method and system of a gas leakage alarm and a gas meter, which is used to realize high-precision, low-false alarm and fast response of gas leakage detection.

[0006] In a first aspect, the present application provides a linkage monitoring method of a gas leakage alarm and a gas meter, which comprises:

[0007] monitoring the target area according to a first time period, and heating and cooling the gas sensor in each monitoring period, and obtaining corresponding first monitoring values and second monitoring values, and calculating and obtaining the gas source of the target area based on a ratio of the second monitoring values to the first monitoring values;

[0008] when the gas source is a gas leakage, generating and activating a camera in the image acquisition device to shoot a gas meter counter in the target area based on a leakage trigger signal, and obtaining a counter image, and also collecting temperature data and pressure data of the gas meter and uploading them to a data processing center;

[0009] the data processing center analyzes the counter image based on an image recognition algorithm, calculates the real-time gas consumption of the gas meter, and dynamically corrects the real-time gas consumption based on the temperature data and the pressure data to generate a corrected gas consumption;

[0010] if the time correlation between the corrected gas consumption and the leakage trigger signal meets any one of the preset abnormal conditions, a linkage control instruction is generated to automatically close the valve of the gas meter and trigger an alarm signal.

[0011] In combination with the first aspect, in a first implementation manner of the first aspect of the present application, obtaining the gas source of the target area comprises:

[0012] when the ratio is less than the minimum value of the first threshold range, it is determined that the gas source of the target area is kitchen waste or food spoilage, and when the ratio is greater than the maximum value of the first threshold range, it is determined that the gas source of the target area is a gas leakage.

[0013] In combination with the first aspect, in a second implementation manner of the first aspect of the present application, obtaining the corresponding first monitoring values and second monitoring values comprises:

[0014] the control unit drives the heating unit of the gas sensor to heat the sensing unit of the gas sensor to a first temperature range through a discontinuous electrical signal to obtain the first monitoring value output by the gas sensor;

[0015] when the first monitoring value is greater than a second threshold value, the control unit adjusts the discontinuous electrical signal parameter of the heating unit of the gas sensor to cool the sensing unit of the gas sensor to a second temperature range to obtain the second monitoring value output by the gas sensor.

[0016] In combination with the first aspect, in a third implementation manner of the first aspect of the present application, obtaining the counter image comprises:

[0017] After the leak trigger signal is generated, the image acquisition device of the gas meter is immediately activated, and during the continuous gas leak, the counter image of the gas meter is acquired multiple times according to the second time period, and a time sequence identifier is added to each image before it is stored in the storage unit.

[0018] In conjunction with the first aspect, in the fourth implementation of the first aspect of this application, calculating the real-time gas consumption of the gas meter includes:

[0019] The display area of ​​the gas meter counter is located using a deep learning model. Optical character recognition is performed on the display area of ​​the gas meter counter to extract the value of the cumulative gas consumption. Based on the time sequence identifier of the gas meter counter image, the continuous cumulative gas consumption values ​​are obtained. Based on the continuous cumulative gas consumption values, the real-time gas consumption of the gas meter is calculated.

[0020] In conjunction with the first aspect, in the fifth implementation of the first aspect of this application, dynamically correcting the real-time gas consumption based on the temperature data and the pressure data includes:

[0021] Based on the ideal gas law, the real-time gas consumption is converted into an equivalent value under standard conditions. Then, a dynamic compensation coefficient is constructed based on the temperature and pressure data. The equivalent value is corrected based on the dynamic compensation coefficient to generate the corrected gas consumption.

[0022] In conjunction with the first aspect, in the sixth implementation of the first aspect of this application, pre-set exception conditions include:

[0023] Condition 1: Within a preset time period after the leakage trigger signal is generated, the growth rate of the corrected gas consumption exceeds the historical benchmark value;

[0024] Condition 2: The initial increase time of the corrected gas consumption is earlier than the generation time of the leak trigger signal, or the time difference between the two exceeds the reasonable response range;

[0025] Condition 3: During the leak triggering period, the pressure data of the gas meter continues to drop, while the corrected gas consumption increases abnormally.

[0026] Condition 4: The instantaneous fluctuation range of the corrected gas consumption exceeds the dynamic safety threshold;

[0027] Condition 5: The temperature data of the gas meter and the corrected gas consumption trend deviate significantly from the historical pattern.

[0028] In conjunction with the first aspect, in the seventh implementation of the first aspect of this application, the method further includes power management:

[0029] activating the image acquisition device when the leakage trigger signal is detected; and setting the image acquisition device to enter the low-power sleep mode after the leakage signal is released.

[0030] In combination with the first aspect, in an eighth implementation form of the first aspect of the application, the first time period is controlled by intelligent interval control, including:

[0031] When the changes in the ambient temperature and humidity are both less than A%, if the leakage trigger signal is not generated in the continuous N detection results, the first time period is gradually extended, and the time period of each extension is less than half of the time period of the last extension, otherwise the first time period remains unchanged; when the change of any one of the ambient temperature and humidity is greater than or equal to A%, if the leakage trigger signal is generated in the recent N detection results, the first time period is shortened to half of the last time period.

[0032] In a second aspect, the application provides a linkage monitoring system of a gas leakage alarm and a gas meter, the system comprising:

[0033] a source detection unit configured to monitor a target area according to a first time period, heat and cool the gas sensor in each monitoring period, and obtain corresponding first and second monitoring values, and calculate and obtain the gas source of the target area based on the ratio of the second monitoring value to the first monitoring value;

[0034] an image shooting unit configured to activate a camera in the image acquisition device to shoot a gas meter counter in the target area and obtain a counter image based on a leakage trigger signal when the gas source is a gas leakage, and upload the temperature data and pressure data of the gas meter to a data processing center;

[0035] a consumption correction unit configured to analyze the counter image based on an image recognition algorithm, calculate the real-time gas consumption of the gas meter, and dynamically correct the real-time gas consumption based on the temperature data and the pressure data to generate a corrected gas consumption at the data processing center;

[0036] a linkage alarm unit configured to automatically close the valve of the gas meter and trigger an alarm signal based on a linkage control instruction if the time correlation between the corrected gas consumption and the leakage trigger signal meets any one of the preset abnormal conditions.

[0037] Compared with the prior art, the application has at least the following advantages:

[0038] The technical scheme provided in the application significantly improves the accuracy of gas leakage detection through innovative technology integration. First, the dual-temperature zone gas sensor dynamic detection technology is adopted, which periodically heats and cools, combined with the sensitivity difference of semiconductor materials to methane and ethane at different temperatures, to distinguish between gas leakage and non-leakage gas sources such as kitchen spoilage, significantly reducing the false positive rate. Second, image recognition and optical character recognition (OCR) technology are introduced, and a deep learning model is used to analyze gas meter counter images in real time, combined with time series data analysis and dynamic temperature and pressure compensation, to eliminate the influence of environmental interference on flow measurement, achieving high-precision dynamic correction of gas consumption. At the same time, based on the cross-validation mechanism of multi-dimensional abnormal conditions, the limitations of single criterion are effectively avoided, ensuring the accuracy of leakage determination. In addition, intelligent power management strategies are adopted, such as low-power sleep mode and dynamic activation mechanism to extend device battery life, and intelligent interval control to optimize detection cycles, reducing sensor energy consumption and wear. Through the cooperation between the above steps, the application not only realizes millisecond-level leakage response and automatic valve control, but also adapts to complex environments such as high altitudes and high temperatures, balancing safety and user experience, providing efficient and reliable technical support for gas safety management. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are some embodiments of the application, and for those skilled in the art, other drawings can be obtained based on these drawings without creative labor.

[0040] Figure 1 An embodiment schematic diagram of the linkage monitoring method of the gas leakage alarm and the gas meter in the embodiment of the application;

[0041] Figure 2 An embodiment schematic diagram of the linkage monitoring method of the gas leakage alarm and the gas meter in the embodiment of the application;

[0042] Figure 3 An embodiment schematic diagram of the linkage monitoring method of the gas leakage alarm and the gas meter in the embodiment of the application;

[0043] Figure 4 An embodiment schematic diagram of the linkage monitoring method of the gas leakage alarm and the gas meter in the embodiment of the application; DETAILED DESCRIPTION

[0044] The embodiments of the present application provide a linkage monitoring method and system of a gas leakage alarm and a gas meter. The terms "first", "second", "third", "fourth" and the like (if any) in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not have to be used to describe a particular order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" or "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0045] For ease of understanding, the specific processes of the embodiments of the present application are described below. Please refer to Figure 1 One embodiment of the linkage monitoring method of the gas leakage alarm and the gas meter in the embodiments of the present application includes the following steps.

[0046] Step S1: monitoring the target area according to a first time period, and in each monitoring period, heating and cooling the gas sensor, and obtaining a first monitoring value and a second monitoring value, calculating and obtaining the gas source of the target area based on the ratio of the second monitoring value to the first monitoring value.

[0047] Specifically, since the gas contains a large amount of methane and a small amount of ethane, whether the gas leaks can be judged by monitoring whether the target area contains methane. However, in places where there is gas, other substances may also release methane, such as: kitchen waste accumulated in the sewer and fermented or food spoilage process will release methane, which will interfere with the judgment of whether the gas in the target area leaks. Therefore, the present application uses a gas sensor to periodically heat and cool the operation, uses a semiconductor material such as SnO2, and uses the difference in sensitivity of methane and ethane at different temperatures to obtain monitoring values in the first temperature range and the second temperature range, such as the first temperature range is the high temperature zone, about 550℃; the second temperature range is the low temperature zone, about 300℃. At high temperature, the methane oxidation reaction is active, which will cause the sensor to output a significant response; while at low temperature, the selective catalysis of ethane is enhanced, and the sensitivity of the sensor to ethane is relatively improved. By analyzing the signal ratio at two temperatures, that is, the ratio of the second monitoring value to the first monitoring value, and combining the preset threshold, it can dynamically identify whether the gas source is a gas leakage. The specific method will be described in detail below. This step can effectively distinguish whether it is a gas leakage or a gas released by other substances through temperature regulation and proportional determination method, reduce the false alarm rate of gas alarm, and generate a high-confidence leakage trigger signal.

[0048] Step S2: When the gas source is a gas leak, generate and activate the camera in the image acquisition device to take pictures of the gas meter counter in the target area based on the leak trigger signal, and obtain the counter image, while also collecting temperature data and pressure data of the gas meter and uploading them to the data processing center.

[0049] Specifically, the generated leak trigger signal activates the camera to collect images of the gas meter counter, and synchronously collects real-time data of embedded temperature sensors, such as thermocouples, and pressure sensors, such as piezoresistive sensors. The temperature sensors and pressure sensors monitor the working conditions of the gas pipeline in real time, which is used for subsequent dynamic correction of gas consumption. All data is packaged and uploaded to the data processing center through the low-power Internet of Things protocol. The data processing center can be a local server, a cloud server, or an edge server, and the specific use can be determined according to the needs. This step provides complete input for subsequent analysis through multi-modal data collection. The image acquisition device includes a camera, a storage unit, a communication unit, etc.

[0050] Step S3: The data processing center analyzes the counter image based on image recognition algorithms, calculates the real-time gas consumption of the gas meter, and dynamically corrects the real-time gas consumption based on temperature data and pressure data to generate the corrected gas consumption.

[0051] Specifically, the data processing center uses a deep learning model to analyze the counter image, identifies the change in the digital value of the mechanical counter, and calculates the real-time gas consumption through time series analysis. Specifically, the convolutional neural network CNN locates the counter digit area in the counter image, uses optical character recognition OCR to extract the numerical value, and verifies the continuity through time series image frame difference to exclude the interference of reflection or stains; at the same time, based on the ideal gas state equation: PV=nRT, the flow under actual temperature and pressure is converted into standard state equivalent value, and a nonlinear compensation model is constructed to eliminate the influence of environmental fluctuations. This step reduces the error rate of the corrected gas consumption through the fusion of physical models and AI algorithms, solves the problems of reading error of traditional mechanical counters and environmental interference, and also adapts to complex environments such as highlands and high temperatures, ensuring the accuracy of measurement results.

[0052] Step S4: If the time correlation between the corrected gas consumption and the leak trigger signal meets any of the preset abnormal conditions, generate and activate the linkage control instruction to automatically close the valve of the gas meter and trigger the alarm signal.

[0053] Specifically, by timing correlation analysis and multi-condition logical judgment of leakage risk, if the corrected gas consumption increases by more than 3 times of the historical average within a short time, such as 5 minutes, after the leakage trigger, or there is a contradiction with the leakage signal timestamp, such as a sharp increase in flow rate before the alarm, or accompanied by abnormal pressure drop, etc., it is determined to be a leakage. The specific judgment conditions will be described in detail below. Then generate a linkage instruction, issue a valve closing signal and verify the execution status; wherein the linkage instruction can also be encrypted before being issued to avoid data tampering. If the closing fails, the standby electromagnetic valve is started or the emergency platform is notified. By multi-dimensional cross verification to avoid misjudgment, support hierarchical response: local alarm, remote notification and forced gas cut, while ensuring safety, reduce interference to normal use of users. Through timing correlation analysis and threshold dynamic adjustment, this step can realize accurate judgment and millisecond-level response of leakage events, and maximize the reduction of explosion or poisoning risk.

[0054] It can be understood that the execution subject of the present application can be a linkage monitoring system of a gas leakage alarm and a gas meter, and can also be a terminal or a server, which is not limited here. The server is taken as an example for description in the embodiments of the present application.

[0055] In the embodiments of the present application, through the cooperation between the above steps, high precision, low false alarm and fast response of gas leakage detection can be realized.

[0056] In a specific embodiment, the process of acquiring the gas source of the target area can specifically include the following steps:

[0057] When the ratio is less than the minimum value of the first threshold range, it is determined that the gas source of the target area is kitchen waste or food spoilage, and when the ratio is greater than the maximum value of the first threshold range, it is determined that the gas source of the target area is gas leakage.

[0058] Specifically, the dynamic response characteristics of the gas sensor under dual-temperature zone detection realize accurate classification of the gas source. The specific dual-temperature zone detection method will be described below. At a high temperature zone of about 550 DEG C, the detection sensitivity of the sensor to methane is significantly higher than that to ethane, and the voltage signal of the first monitoring value of 3000 ppm methane is 125 mV; at a low temperature zone of about 300 DEG C, the detection sensitivity of the sensor to ethane is relatively improved, and the sensitivity to methane is reduced, and the voltage signal of the second monitoring value of 3000 ppm methane can be 30 mV or 66 mV. By calculating the signal ratio at the two temperatures: Z = second monitoring value / first monitoring value, and combining the preset first threshold range, such as Z = 30 / 125 < 0.3, it is determined that the kitchen waste is a kitchen waste, Z = 66 / 125 > 0.5 is determined to be a gas leakage, and the gas source is dynamically distinguished. For example, the gas generated by kitchen waste is mainly hydrogen sulfide and ammonia, and the second monitoring value is high in the low temperature zone due to the active catalytic oxidation reaction, and the first monitoring value is small due to the low methane content, and the Z value tends to the lower limit; when the gas leaks, methane and ethane coexist, and the high first monitoring value in the high temperature zone and the second monitoring value in the low temperature zone form a high ratio. The first threshold range is dynamic and can be adjusted in combination with environmental factors and long-term operation data. The principle of the method is to utilize the temperature sensitivity of the semiconductor material and the difference in activation energy of different gas oxidation reactions to distinguish whether the methane source is kitchen waste or food spoilage or gas leakage through dual-temperature zone detection. In practical application, differential response can be performed according to the determination result: if it is a kitchen waste, local ventilation or odor reminder is triggered; if it is a gas leakage, a leakage trigger signal is generated, and further accurate determination and alarm are performed in combination with the gas meter counter. The scheme can reduce the false alarm rate in complex environments such as kitchens, and can also avoid unnecessary gas meter shutdown caused by food fermentation and other non-leakage events, and improve user experience.

[0059] In a specific embodiment, referring to Figure 2 As shown in the figure, the process of obtaining the corresponding first monitoring value and second monitoring value can specifically include the following steps: the control unit controls the heating unit of the gas sensor to heat the sensing unit of the gas sensor to the first temperature range through the discontinuous electric signal, and obtains the first monitoring value output by the gas sensor; when the first monitoring value is greater than the second threshold value, the control unit adjusts the discontinuous electric signal parameter of the heating unit of the gas sensor, and cools the sensing unit of the gas sensor to the second temperature range, and obtains the second monitoring value output by the gas sensor.

[0060] The gas sensor has different sensitivities to the first gas and the second gas in different temperature ranges. The sensor is a semiconductor gas sensor having a sensing unit and a heating unit, wherein the surface of the gas sensor is further covered with a palladium catalyst layer for enhancing selective detection of the first gas and the second gas. The first gas is methane, and the second gas can be ethane or other gases in fuel gas.

[0061] Specifically, the control unit drives the heating unit with a pulsed electrical signal. In a first time period, the sensing unit is rapidly heated to a first temperature range, such as between 500-600℃, with high-frequency pulses. The high sensitivity of the semiconductor material, such as SnO2-Pd composite layer, to methane at high temperatures is used to obtain a first monitoring value. If the first monitoring value exceeds a second threshold value, such as corresponding to a methane concentration ≥1000ppm, the control unit immediately switches to a low-frequency pulse mode. The heating power is reduced to allow the sensing unit to naturally cool to a second temperature range, such as between 250-350℃. At this time, the oxidation reaction of ethane, propane and other long-chain hydrocarbons is enhanced under Pd catalysis, and the sensor outputs a second monitoring value. This process can complete the dual-temperature zone switching within 5 seconds through adaptive adjustment of the electrical signal parameters, while avoiding the energy waste caused by traditional continuous heating. In practical applications, the second detection is triggered only when the first monitoring value exceeds the second threshold value, which can effectively eliminate the false response of interfering gases such as hydrogen sulfide or ethanol in single-temperature detection. For example, the evaporation of kitchen alcohol only triggers a signal in the high-temperature zone, and there is no significant change in the low-temperature zone. Combined with the proportional judgment of the two monitoring values, the recognition of fuel gas leakage can be accurately improved.

[0062] In a specific embodiment, the process of obtaining the counter image can specifically include the following steps:

[0063] After the leakage trigger signal is generated, the image acquisition device of the gas meter is activated immediately, and the counter image of the gas meter is obtained multiple times in a second time period during the continuous leakage of the gas, and is stored in the storage unit after adding a time sequence identifier respectively.

[0064] Specifically, after the leakage trigger signal is generated, the image acquisition device of the gas meter is activated immediately, and a high-frequency image capture process is started: first, an instant snapshot of the first counter image is performed to ensure that the key data in the initial stage of leakage is retained; then during the continuous leakage of the gas, multiple frames of counter images are continuously captured at a preset second time period, each frame of image is embedded with a time sequence identifier accurate to the millisecond level, and stored in the local storage unit. The second time period is shorter than the first time period. The time sequence identifier provides a time anchor point for subsequent analysis, supporting the alignment and trend tracking of cross-period data. By densely sampling the dynamic changes of the counter during the leakage process, such as abnormal digital jump rate and mechanical pointer jitter, and combining the time sequence information to construct a time series model of gas consumption, the ability to describe the leakage evolution process is enhanced. Through high-frequency image acquisition and timestamp marking, this method can accurately identify short-term flow fluctuations such as sudden leakage and exclude false identification caused by single-frame image reflection or contamination, while providing a complete data chain for leakage diffusion simulation and responsibility tracing. Time series data can also be used to train adaptive algorithms to optimize the second time period setting in different leakage scenarios, such as extending the period for small leaks and shortening the period for large leaks, further improving response sensitivity. In addition, the counter image can be compressed and encrypted when transmitted to the data processing center, on the one hand to reduce the occupied space of the counter image and improve transmission efficiency, and on the other hand to improve the security during transmission.

[0065] In a specific embodiment, the process of calculating the real-time gas consumption of the gas meter can specifically include the following steps:

[0066] The display area of the gas meter counter is located by the deep learning model, optical character recognition is performed on the display area of the gas meter counter, the value of the cumulative gas consumption is extracted, and based on the time sequence identifier of the gas meter counter image, the continuous value of the cumulative gas consumption is obtained. Based on the continuous value of the cumulative gas consumption, the real-time gas consumption of the gas meter is calculated.

[0067] Specifically, by deep learning model, such as attention mechanism based convolutional neural network, the digital display area of the gas meter counter is accurately positioned, and the background such as the dial stain and the interference of the reflection are excluded, and then the optical character recognition (OCR) algorithm is used to analyze the digital sequence in the display area, and the cumulative gas consumption value is extracted. Both of the above methods belong to the prior art, and will not be described here. In combination with the time sequence identifier embedded in the image, the cumulative values of the continuous multiple frames are arranged in time sequence to construct time series data, and the gas consumption rate per unit time is derived in real time through difference calculation or sliding window average method. This process uses the continuity verification mechanism of time series data to automatically eliminate abnormal values caused by image blur and instantaneous obstruction, ensuring the reliability of the calculation results. Through the integration of deep learning and OCR technology, the present application can adapt to different types of gas meter digital display styles, such as Song Ti and Black Body, etc., to improve the accuracy of character recognition; time series data analysis further eliminates single measurement random error, reduces the error rate of real-time flow calculation. At the same time, the dynamic monitoring of the consumption trend can provide a quantitative basis for the identification of leakage modes, such as slow leakage and sudden rupture, which can significantly improve the intelligent level of leakage judgment and grading response.

[0068] In a specific embodiment, the process of dynamically correcting the real-time gas consumption based on temperature data and pressure data can specifically include the following steps:

[0069] Based on the ideal gas state equation, the real-time gas consumption is converted into an equivalent value under standard conditions, and a dynamic compensation coefficient is constructed based on the temperature data and the pressure data, and the equivalent value is corrected based on the dynamic compensation coefficient to generate the corrected gas consumption.

[0070] Specifically, based on the ideal gas state equation: PV = nRT, the real-time gas consumption is converted from the measured value under the actual temperature and pressure conditions into an equivalent value under standard conditions, such as 0°C and 1 standard atmospheric pressure, to eliminate the influence of environmental fluctuations on volume measurement; then, a dynamic compensation coefficient is constructed by real-time acquisition of temperature data and pressure data, which reflects the difference in gas density ratio or compression factor between the current working condition and the standard state, and the equivalent value is corrected by combining a nonlinear correction model to generate the actual gas consumption. Dynamically adapt to gas state changes, such as high temperature expansion and low pressure contraction, and make secondary compensation for the deviation of actual gas and ideal gas behavior to ensure the consistency of measurement under different environments, such as high altitude and extreme temperature. Through the dual correction of physical model and data driven, the measurement error of gas consumption can be reduced, and the leakage detection sensitivity can be improved, providing a high reliability data basis for safety monitoring.

[0071] In a specific embodiment, the preset abnormal condition can specifically include:

[0072] Condition 1: The growth rate of the corrected gas consumption exceeds the historical baseline value, e.g. 3 times of the standard deviation calculated based on the past 30 days data, within a preset time period after the generation of the leak trigger signal. The decision logic is to verify whether the sudden consumption surge is synchronized with the leak signal by combining the time series analysis, to exclude the short-term fluctuations caused by normal user behavior.

[0073] Condition 2: The starting time of the corrected gas consumption growth is earlier than the generation time of the leak trigger signal, or the time difference exceeds the reasonable response range, e.g. 10 seconds. The causal relationship between the leak signal and the consumption change is verified by time axis alignment, to detect the system clock desynchronization or sensor signal delay problem.

[0074] Condition 3: During the leak trigger period, the pressure data of the gas meter continuously decreases, e.g. below 20% of the normal working pressure, while the corrected gas consumption abnormally increases. The physical contradiction between pressure drop and flow increase is analyzed by combining the ideal gas state equation: PV = nRT, to identify the risk of pipe damage or valve failure.

[0075] Condition 4: The instantaneous fluctuation amplitude of the corrected gas consumption exceeds the dynamic safety threshold. The safety threshold is adaptively adjusted based on the gas type, pipeline pressure and environmental temperature. The fluctuation degree is quantified by sliding window statistics, e.g. root mean square error, to exclude single measurement noise interference.

[0076] Condition 5: The temperature data of the gas meter significantly deviates from the historical pattern of the corrected gas consumption change trend, e.g. temperature rises sharply but consumption does not increase synchronously. The temperature-flow correlation is analyzed by using a machine learning model to identify sensor failure or external heat source interference.

[0077] Specifically, the comprehensive determination of the leakage risk is realized by presetting multiple-dimensional abnormal conditions, to reduce the false positive rate while covering different types of leakage scenarios. The application can adapt to different user habits, e.g. automatically relaxing the baseline during peak gas usage period, to reduce the interference on normal use while ensuring safety.

[0078] In a specific embodiment, the method performed further comprises power management, specifically comprising the following steps:

[0079] When no leak trigger signal is detected, the image acquisition device is in low-power sleep mode; when a leak trigger signal is detected, the image acquisition device is activated; after the leak signal is removed, the image acquisition device is set to enter low-power sleep mode.

[0080] Specifically, the running state of the image acquisition device is dynamically regulated by the intelligent power management mechanism: when no leakage trigger signal is detected, the camera, communication module and processor of the image acquisition device enter a low-power sleep mode, only the core sensor, the gas detection unit, is retained to maintain the basic monitoring function with a micro-current, and the leakage signal is monitored in real time through the hardware interrupt circuit; when the leakage trigger signal is generated, the sleep module is immediately awakened, the camera is activated for high-frequency image acquisition, and the communication module is started to upload data to the data processing center to ensure full-period data capture of the leakage event; after the leakage signal is removed, a preset protection period, such as 5 minutes or 10 minutes, is delayed to confirm that there is no secondary leakage risk, and then the high-power components are turned off and the sleep mode is re-entered. This method can achieve the optimal balance between energy consumption and safety monitoring. Reducing the standby power consumption of the device in a non-leakage state significantly extends the endurance of the wireless gas meter, while ensuring zero delay in leakage response.

[0081] In a specific embodiment, the first time period adopts intelligent interval control, which can specifically include the following steps:

[0082] When the changes in the ambient temperature and humidity are both less than A%, if the leakage trigger signal is not generated in the continuous N detection results, the first time period is gradually extended, and the time period is extended by less than half of the previous time period each time, otherwise the first time period remains unchanged; when the change in any one of the ambient temperature and humidity is greater than or equal to A%, if the leakage trigger signal is generated in the recent N detection results, the first time period is shortened to half of the previous time period. Wherein, A represents a positive integer greater than or equal to 10 and less than or equal to 50; N represents a positive integer greater than or equal to 2 and less than or equal to 20.

[0083] Specifically, by dynamically controlling the first time period, the number and time of high-temperature heating can be significantly reduced, the life of the gas sensor can be extended to 2-3 times of the original design, and the overall energy consumption can be reduced.

[0084] Embodiment two:

[0085] The above describes the linkage monitoring method of the gas leakage alarm and the gas meter in the embodiment of the application, and the linkage monitoring system of the gas leakage alarm and the gas meter in the embodiment of the application is described below, Figure 3 is a schematic diagram of one of the scenarios of the linkage monitoring of the gas leakage alarm and the gas meter. Referring to Figure 4 , one embodiment of the linkage monitoring system of the gas leakage alarm and the gas meter in the embodiment of the application includes:

[0086] The source detection unit is configured to monitor the target area in a first time period, heat and cool the gas sensor in each monitoring period, and obtain corresponding first monitoring values and second monitoring values, and calculate and obtain the gas source of the target area based on the ratio of the second monitoring values to the first monitoring values.

[0087] The image shooting unit is configured to, when the gas source is a gas leakage, generate and activate a camera in the image acquisition device to shoot a gas meter counter in the target area based on a leakage trigger signal, and obtain a counter image, and also acquire temperature data and pressure data of the gas meter and upload them to the data processing center.

[0088] The consumption correction unit is configured to calculate the real-time gas consumption of the gas meter based on image recognition algorithm analysis of the counter image by the data processing center, and dynamically correct the real-time gas consumption based on the temperature data and the pressure data to generate the corrected gas consumption.

[0089] The linkage alarm unit is configured to, if the time correlation between the corrected gas consumption and the leakage trigger signal meets any one of the preset abnormal conditions, generate and automatically close the valve of the gas meter and trigger an alarm signal based on a linkage control instruction.

[0090] Through the cooperation of the above-mentioned components, high precision, low false alarm and fast response of gas leakage detection can be achieved.

[0091] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-mentioned system, system and unit can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0092] The integrated unit, if realized in the form of a software function unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0093] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for linking a gas leak alarm with a gas meter for monitoring, characterized in that, The method includes: The target area is monitored according to the first time period, and the gas sensor is heated and cooled in each monitoring period to obtain the corresponding first monitoring value and second monitoring value. The gas source of the target area is calculated and obtained based on the ratio of the second monitoring value to the first monitoring value. Obtaining the corresponding first and second monitoring values ​​includes: the control unit drives the heating unit of the gas sensor to heat the sensing unit of the gas sensor to a first temperature range through a discontinuous electrical signal, and obtains the first monitoring value output by the gas sensor; when the first monitoring value is greater than a second threshold, the control unit adjusts the discontinuous electrical signal parameter of the heating unit of the gas sensor to cool the sensing unit of the gas sensor to a second temperature range, and obtains the second monitoring value output by the gas sensor. When the gas source is a gas leak, a leak trigger signal is generated and activated to activate the camera in the image acquisition device to capture the gas meter counter in the target area and obtain the counter image. At the same time, the temperature data and pressure data of the gas meter are also collected and uploaded to the data processing center. The data processing center analyzes the counter image based on an image recognition algorithm, calculates the real-time gas consumption of the gas meter, and dynamically corrects the real-time gas consumption based on the temperature data and the pressure data to generate the corrected gas consumption. If the time correlation between the corrected gas consumption and the leak trigger signal meets any preset abnormal condition, then a linkage control command is generated to automatically close the valve of the gas meter and trigger an alarm signal.

2. The method according to claim 1, characterized in that, Obtaining the gas source of the target area includes: When the ratio is less than the minimum value of the first threshold range, the gas source of the target area is determined to be kitchen waste or food spoilage; when the ratio is greater than the maximum value of the first threshold range, the gas source of the target area is determined to be gas leakage.

3. The method according to claim 1, characterized in that, Obtain the counter image, including: After the leak trigger signal is generated, the image acquisition device of the gas meter is immediately activated, and during the continuous gas leak, the counter image of the gas meter is acquired multiple times according to the second time period, and a time sequence identifier is added to each image before it is stored in the storage unit.

4. The method according to claim 1, characterized in that, Calculating the real-time gas consumption of the gas meter includes: The display area of ​​the gas meter counter is located using a deep learning model. Optical character recognition is performed on the display area of ​​the gas meter counter to extract the value of the cumulative gas consumption. Based on the time sequence identifier of the gas meter counter image, the continuous cumulative gas consumption values ​​are obtained. Based on the continuous cumulative gas consumption values, the real-time gas consumption of the gas meter is calculated.

5. The method according to claim 1, characterized in that, Dynamically correcting the real-time gas consumption based on the temperature data and the pressure data includes: Based on the ideal gas law, the real-time gas consumption is converted into an equivalent value under standard conditions. Then, a dynamic compensation coefficient is constructed based on the temperature and pressure data. The equivalent value is corrected based on the dynamic compensation coefficient to generate the corrected gas consumption.

6. The method according to claim 1, characterized in that, Preset exception conditions include: Condition 1: Within a preset time period after the leakage trigger signal is generated, the growth rate of the corrected gas consumption exceeds the historical benchmark value; Condition 2: The initial increase time of the corrected gas consumption is earlier than the generation time of the leak trigger signal, or the time difference between the two exceeds the reasonable response range; Condition 3: During the leak triggering period, the pressure data of the gas meter continues to drop, while the corrected gas consumption increases abnormally. Condition 4: The instantaneous fluctuation range of the corrected gas consumption exceeds the dynamic safety threshold; Condition 5: The temperature data of the gas meter and the corrected gas consumption trend deviate significantly from the historical pattern.

7. The method according to claim 1, characterized in that, The method also includes power management: When no leakage trigger signal is detected, the image acquisition device is put into a low-power sleep mode; when the leakage trigger signal is detected, the image acquisition device is activated; after the leakage signal is released, the image acquisition device is set to enter the low-power sleep mode.

8. The method according to claim 1, characterized in that, The first time period employs intelligent interval control, including: When the changes in ambient temperature and humidity are both less than A%, if no leakage trigger signal is generated in N consecutive detection results, the first time period is gradually extended, and the extension of the time period each time is less than half of the previous time period; otherwise, the first time period remains unchanged. When the change in either ambient temperature or humidity is greater than or equal to A%, if the leakage trigger signal has been generated in any of the last N detection results, the first time period is shortened to half of the previous time period.

9. A gas leak alarm and gas meter linkage monitoring system, used to implement the gas leak alarm and gas meter linkage monitoring method as described in any one of claims 1-8, characterized in that, The system includes: The source detection unit is used to monitor the target area according to a first time period, and in each monitoring period, heat and cool the gas sensor, and obtain the corresponding first monitoring value and second monitoring value, calculate and obtain the gas source of the target area based on the ratio of the second monitoring value to the first monitoring value; The image capturing unit is used to generate and, based on a leak trigger signal, activate the camera in the image acquisition device to capture the gas meter counter in the target area when the gas source is a gas leak, and acquire the counter image. At the same time, it also acquires the temperature data and pressure data of the gas meter and uploads them together to the data processing center. The consumption correction unit is used by the data processing center to parse the counter image based on the image recognition algorithm, calculate the real-time gas consumption of the gas meter, and dynamically correct the real-time gas consumption based on the temperature data and the pressure data to generate the corrected gas consumption. The linkage alarm unit is used to generate and automatically close the valve of the gas meter and trigger an alarm signal based on the linkage control command if the time correlation between the corrected gas consumption and the leakage trigger signal meets any preset abnormal condition.

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